Human Fc <sub>ε</sub> R II and IgE-Binding Factors
Bibliographic record
Abstract
The low-affinity receptor for IgE (FcεR II) is mainly expressed on B lymphocytes, although it may also be found on some monocytes, eosinophils, and platelets. The presence of FcεR II on T cells is still controversial, but our results demonstrate that it is expressed on some HTLV-I-transformed T lymphocytes, and they strongly suggest that it may be found on a small proportion of normal T cells. FcεR II is a 45-KD glycoprotein containing one N-linked carbohydrate of complex type, O-linked carbohydrates, and sialic acid residues. Fc II is cleaved into soluble fragments with molecular weights of 37, 33, 25, and 12 KD, the first three retain the ability of binding to IgE, i.e., they are IgE-binding factors (IgE-BFs). The enzymes involved in their proteolytic cleavage are cell bound. The cDNA coding for FcεR II was cloned and functionally expressed. The predicted sequence has no homology with that of murine IgE-BFs which are of T cell origin. However, there is a striking homology with several animal lectins, and since the IgE-binding site is located in the homology region, it is possible that it binds to IgE via the carbohydrates expressed on the Fc region of this immunoglobulin. The expression of FcεR II on B cells and the release of IgE-BFs are upregulated by interleukin 4 and suppressed by gamma and alpha interferons. The finding that FcεR II is identical to CD23, known as a B cell activation marker, suggests that FcεR II or its soluble fragments are involved in B cell activation. Accumulating evidence suggests that some soluble fragments of FcεR II display B cell growth factor activity. Finally, several observations strongly suggest that IgE-BFs regulate human IgE synthesis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".